Marktechpost AI Launches GPU Leaderboard and the Deploy It Chrome Extension

MarkTechPost has launched GPU Leaderboard, a free site comparing rentable cloud GPU prices for AI inference, plus a Chrome extension called Deploy It. The site says it ranks 201 live offers from 24 providers by price per GPU-hour, using on-demand and spot prices read from providers' own pricing pages.

Its default example is striking: an eight-H100 run for 72 hours at 90% utilization costs $967.68 at the cheapest listed provider and $3,545.28 at the most expensive, with a median of $1,716.48 across 15 providers. Same hardware, more than a threefold spread.

Start with the disclosure. This is a media company writing about its own launch, so we treat the claims as a product announcement rather than independent reporting. The prices come from the tool itself, and the write-up openly concedes that coverage and daily refresh are its main gaps against older trackers. That honesty is welcome, and it also tells us the snapshot can go stale fast.

Still, the underlying point is useful and worth repeating. GPU pricing for inference is opaque and wildly uneven. A team that rents the first option it finds can pay several times what it needs to. Tools that put the full spread in front of developers are good for the market, because transparency is the cheapest form of competition.

The smartest detail is the calculator's 'real' cost per used GPU-hour. Idle time is still billed, so a $1.68 rate at 90% utilization works out to about $1.87 of actual use. That's the kind of number that blows up budgets quietly, and making it visible is genuinely helpful for small teams.

The Chrome extension is a sensible idea: on Hugging Face model pages it estimates VRAM needs at different precisions and shows the cheapest GPUs that fit, and it attempts similar estimates on GitHub repos. We'd use those estimates as a starting point, not a guarantee; real memory needs depend on context length, batch size and serving stack.

One limit to keep in mind: the cheapest hourly rate isn't the whole story. Availability, reliability, support and data location all matter, especially for production workloads. A price ranking can push buyers toward providers they haven't vetted. Used carefully, though, this is the kind of small infrastructure tool that makes AI cheaper to run.

Cloud GPU rental has become a crowded market of large clouds and specialist providers, with prices varying by tier, region and availability. Several older trackers already compare GPU prices; this entrant focuses on inference runs.